264 Increased Hand Hygiene Observations Add Validity to Infection Control Data But How to Achieve in a Busy Hospital World?

Friday, March 19, 2010
Grand Hall (Hyatt Regency Atlanta)
Lisa M. Cooper, RN, BSN , Duke University Medical Center, Durham, NC
Mary A. Oden, RN, MSN-CL , Cleveland Clinic Health System, Cleveland, OH
Brandon K. Elliott , Duke University Medical Center, Durham, NC
Jeffrey A. Harger , Duke University Medical Center, Durham, NC
Deverick J. Anderson, MD, MPH , Duke University Medical Center, Durham, NC
Background: Historically the percentage of hand hygiene (HH) compliance at acute care facilities is routinely 40%-50%. At Duke University Medical Center (DUMC), HH rates were inconsistent, with rates of 16-36% prior to patient contact and 42-55% after patient contact during 2007 -2008.  As a result of this variation and concern about low numbers of observations (obs.), unit leadership was not convinced by our data.

Objective:   To develop a mechanism to improve monitoring of HH compliance rates throughout DUMC

Methods:   The Infection Control and Epidemiology Department (ICE) collaborated with Performance Services (PS) to develop a method to 1) increase our total number of obs., 2) improve our HH auditing process, and 3) provide ICE with the ability to stratify audit information and report rates back to hospital and unit leaders.  PS introduced a hand held device, called an Enterprise Digital Assistant (EDA). At the same time, administration provided temporary support to hire Nursing Care Assistants (NCAs) to record HH obs. on the EDA.  The obs. were immediately transmitted to a website developed by PS for unit leadership to see unit-specific and practitioner-specific data in real time.  We implemented this program April of 2009.

Results: Prior to implementing our HH observation program, we obtained approximately 75-100 HH obs. per month for the entire hospital.  After implementing the program, we obtained an average of 3309 (± SD 2210) HH obs. per month.  In total, we observed 23,164 HH opportunities of which 20,054 (87%) were correct during the 7 months since starting the program.  After roll out of our observation program and a hospital-wide HH campaign, rates of HH compliance increased to greater than 97.5% (n=1,153 correct HH/1,183 observations.).  We were able to stratify our data for more than 40 healthcare locations and 14 different healthcare worker (HCW) categories.  Rates of HH varied by type of HCW.  The top 3 groups of HCW were Medical Assistants, Nurse Practitioners and Physical Therapists (compliance rates= 96 – 100%).  The 3 groups that showed the lowest rates of compliance were technicians, Medical Students, and Physicians (17-81%). Over months 3 - 7 following rollout, rates of HH compliance decreased to 85% (n=18,901 correct HH/21,981 observations). 

Conclusions: We were able to increase the number of obs. of HH compliance throughout the hospital for specific units, and for specific groups of HCW. It enabled us to overcome the common concern regarding HH compliance data derived from few observations. In addition, we were able to more robustly identify specific units and personnel for additional education.  While the initial response to the HH website was positive, our rate of compliance eventually dropped, though not back to baseline. We received budgetary approval from the hospital CEO to hire and maintain six HH auditors to continue our HH observation program.